Artificial intelligence in the service of fraudsters: how neural networks "scam" gullible Russians
The cryptocurrency and digital technology market is developing rapidly, but alongside it, scam schemes are also evolving. Today, fraudsters actively use artificial intelligence algorithms to "poison" search engines and create fake trading platforms. Ordinary users who trust recommendations from chatbots and neural networks are increasingly becoming victims of such schemes.
How does the "data poisoning" scheme work?
The deception mechanism is built on so-called "data poisoning." Attackers pre-fill the internet with fake reviews, automatically generated forum posts, and fictitious data for indexing. The goal is to distort the operation of recommendation algorithms, making them perceive a fraudulent site as a reliable seller.
Most often, clothing and furniture stores that masquerade as well-known brands that have recently ceased operations are targeted. Fraudsters copy the brand style, images, and product descriptions, and to attract victims, they promise discounts of up to 80%. Chatbots trained on such data begin directing users to fake resources created to steal confidential information and money.
How to protect yourself?
The main protective tool is cross-verification. Before placing an order based on a chatbot recommendation, it is worth comparing the obtained data on other search platforms and finding the official original source of information.
It is important to remember the limitations of the technology. Artificial intelligence algorithms sometimes produce outdated and irrelevant data. Therefore, it is wiser to perceive an AI recommendation as a starting point for your own verification, rather than as a ready-made guide to action.
Cryptalist expert opinion: This scheme is just the tip of the iceberg. In the world of cryptocurrencies and DeFi, "data poisoning" can be used to promote scam tokens and fake NFT projects. Always check smart contract addresses and use only verified data aggregators. Trust in AI should be reasonable, not blind.